Cystic fibrosis (CF) is a genetic disease characterized by airway infection and inflammation with early death resulting from chronic airway disease. Pseudomonas aeruginosa is the most important pathogen in CF airway infections and anti-pseudomonal antibiotics have long demonstrated efficacy in decreasing morbidity and mortality in CF. However, other antibiotics--such as azithromycin--that do not have classical in vitro antimicrobial activity against P. aeruginosa have demonstrated clinical efficacy. A recent clinical trial of azithromycin in the US (for which my laboratory performed quantitative microbiology) demonstrated improvement in lung function and decreased rate of pulmonary exacerbation in those patients who received azithromycin (N = 87) compared with those who received placebo (N = 98), in the absence of a quantitative anti-pseudomonal effect. The mechanism of this activity is not understood, but may be caused by host effects, antibacterial effects or a combination of the two. I have subsequently examined study isolates for an antibiofilm effect and demonstrated no correlation with clinical response. Thus, I hypothesize that azithromycin affects gene expression in P. aeruginosa, which may result in decreased inflammation and improved lung function. Three aims are proposed to test that hypothesis. The first of these is to use gene expression arrays to identify genes in strain PAO1 that are regulated by growth in sub-MIC concentrations of azithromycin. Subsequently, the patient isolates from the US trial of azithromycin in CF will be used to determine whether clinical response to the drug correlates with the presence of azithromycin-regulated genes. Finally, differences in gene regulation between those isolates from responders and non-responders will be examined. The data will be analyzed to determine whether there are specific azithromycin-regulated genes whose expression, or lack of it, is correlated with the CF response to azithromycin therapy. It is hoped that elucidation of this mechanism of action may result in other novel therapies. Additionally, specific markers may be identified to predict CF patient response to azithromycin, thus preventing ongoing treatment with ineffective therapy.